Color saturation
In colorimetry and color theory, colorfulness, chroma, and saturation are related concepts referring to the intensity of a specific color. More technically, colorfulness is the perceived difference between the color of some stimulus and gray, chroma is the colorfulness of a stimulus relative to the brightness of a stimulus that appears white under similar viewing conditions, and saturation is the colorfulness of a stimulus relative to its own brightness.Mark D. Fairchild. “Color Appearance Models: CIECAM02 and Beyond”. Slides from a tutorial at the IS&T/SID 12th Color Imaging Conference. 9 November 2004. Retrieved 19 September 2007. Though this general concept is intuitive, terms such as chroma, saturation, purity, and intensity are often used without great precision, and even when well-defined depend greatly on the specific color model in use. A highly colorful stimulus is vivid and intense, while a less colorful stimulus appears more muted, closer to gray. With no colorfulness at all, a color is a “neutral” gray. With three attributes—colorfulness (or chroma or saturation), lightness (or brightness), and hue—any color can be described. Saturation Saturation is one of three coordinates in the HSL and HSV color spaces. Note that virtually all computer software implementing these spaces use a very rough approximation to calculate the value they call "saturation", such as the formula described for HSV and this value has little, if anything, to do with the description shown here. The saturation of a color is determined by a combination of light intensity and how much it is distributed across the spectrum of different wavelengths. The purest color is achieved by using just one wavelength at a high intensity, such as in laser light. If the intensity drops, so does the saturation. To desaturate a color in a subtractive system (such as watercolor), you can add white, black, gray, or the hue's complement. Various correlates for saturation follow. ; CIELUV : The chroma normalized by the luminance: : s_{uv}=13 \sqrt{(u'-u'_n)^2+(v'-v'_n)^2}=\frac{C^*_{uv}}{L^*} where (u'_n,v'_n) is the chromaticity of the white point, and the L*C*h color space is defined below. , page 88. ; CIECAM02 : The square root of the colorfulness divided by the brightness: : s=\sqrt{M/Q} This definition is inspired by experimental work done with the intention of remedying CIECAM97s's poor performance. It should be noted that M is proportional to the chroma C ( M=CF_L^{0.25} ), thus the CIECAM02 definition bears some similarity to the CIELUV definition. An important difference is that the CIECAM02 model accounts for the viewing conditions through the parameter F_L . Excitation purity The excitation purity (purity for short) of a stimulus is its difference from the illuminant's white point relative to the furthest point on the chromaticity diagram with the same hue (dominant wavelength for monochromatic sources); using the CIE 1931 color space: : p_e = \sqrt{\frac{(x - x_n)^2 + (y - y_n)^2}{(x_I - x_n)^2 + (y_I - y_n)^2}} where (x_I,y_I) is the chromaticity of the white point and (x_n,y_n) is the point on the perimeter whose line segment to the white point contains the chromaticity of the stimulus. Different color spaces, such as CIELAB or CIELUV may be used, and will yield different results. Chroma in CIE 1976 L*a*b* and L*u*v* color spaces The naïve definition of saturation does not specify its response function. In the CIE XYZ and RGB color spaces, the saturation is defined in term of additive color mixing, and has the property of being proportional to any scaling centered at white or the white point illuminant. However, both color spaces are nonlinear in terms of psychovisually perceived color differences. It is also possible, and sometimes desirable to define a saturation-like quantity that is linearized in term of the psychovisual perception. In the CIE 1976 L*a*b* and L*u*v* color spaces, the unnormalized chroma is the radial component of the cylindrical coordinate CIE L*C*h (luminance, chroma, hue) representation of the L*a*b* and L*u*v* color spaces, also denoted as CIE L*C*h(a*b*) or CIE L*C*h for short, and CIE L*C*h(u*v*). The transformation of (a^{*}, b^{*}) to (C^{*}, h) is given by: : C^{*} = \sqrt{a^{*2} + b^{*2}} : h = \arctan \frac{b^{*}}{a^{*}} and analogously for CIE L*C*h(u*v*). The chroma in the CIE L*C*h(a*b*) and CIE L*C*h(u*v*) coordinates has the advantage of being more psychovisually linear, yet they are non-linear in the in term of linear component color mixing. And therefore, chroma in CIE 1976 L*a*b* and L*u*v* color spaces is very much different from the traditional sense of "saturation". Chroma in color appearance models Another, psychovisually even more accurate, but also more complex method to obtain or specify the saturation is to use the color appearance model, like CIECAM. The chroma component of the JCh (lightness, chroma, hue) coordinate, and becomes a function of parameters like the chrominance and physical brightness of the illumination, or the characteristics of the emitting/reflecting surface, which is also psychovisually more sensible. Comparison Image:Surfing in Hawaii.jpg|Original image Image:Surfing in Hawaii (retouched).jpg|Contrast and saturation increased See also * Achromatic color * Chromaticity * Color perception * Hue * Luminance (relative) References *Adkins, W. S. (1910). Review of Ueber die Gefalligkeit der Sattigungsstufen der Farben: Psychological Bulletin Vol 7(7) Jul 1910, 247. *Angel, C. L. (2004). The effect of rods on perceptive field size at 10 eccentricity in the four retinal quadrants. Dissertation Abstracts International: Section B: The Sciences and Engineering. *Ball, R. J., & Bartley, S. H. (1966). Changes in brightness index, saturation, and hue produced by luminance--wavelength--temporal interactions: Journal of the Optical Society of America 56(5) 1966, 695-698. *Bimler, D. L., & Paramei, G. V. (2004). Luminance-dependent hue shift in protanopes: Visual Neuroscience Vol 21(3) May-Jun 2004, 403-407. *Breive, K., Vaitkevicius, G., Stanikunas, R., Svegzda, A., Kulikowski, J. J., & Al-Attar, Z. (1999). Studies of color constancy: Sensory Systems Vol 13(4) Oct-Dec 1999, 271-278. *Brown, D. W. (1964). Two-color mixtures: I. Broad-band filters: Journal of Psychology: Interdisciplinary and Applied 58(1) 1964, 89-105. *Camgoz, N., Yener, C., & Guvenc, D. (2004). Effects of Hue, Saturation, and Brightness: Part 2: Attention: Color Research and Application Vol 29(1) Feb 2004, 20-28. *Capilla, P., Luque, M. J., Gomez, J., & Palomares, A. (2001). On saturation and related parameters following Guth's ATD colour-vision model: Color Research and Application Vol 26(4) Aug 2001, 305-321. *Delabarre, E. B. (1895). Ueber das sogenannte Purkinje'sche Phanomen: Psychological Review Vol 2(5) Sep 1895, 518-521. *Franklin, C. L. (1896). Color Saturation and its Quantitative Relations: Psychological Review Vol 3(4) Jul 1896, 451-452. *Fuller, S., & Carrasco, M. (2006). Exogenous attention and color perception: Performance and appearance of saturation and hue: Vision Research Vol 46(23) Nov 2006, 4032-4047. *Hess, R. F., Dakin, S. C., & Field, D. J. (1998). Rapid communication: The role of "contrast enhancement" in the detection and appearance of visual contours: Vision Research Vol 38(6) Mar 1998, 783-787. *Holmberg, L. (1964). Psychophysical experiments on colour saturation: Psychological Research Bulletin 4(4) 1964, 36. *Holmberg, L. (1965). Discontinuity in the subjective scale of color saturation as a result of a shift of instruction: Psychological Research Bulletin 5(3) 1965, 2-8. *Hunt, R. W. G., Li, C. J., & Luo, M. R. (2003). Dynamic Cone Response Functions for Models of Colour Appearance: Color Research and Application Vol 28(2) Apr 2003, 82-88. *Indow, T., & Stevens, S. S. (1966). Scaling of saturation and hue: Perception & Psychophysics 1(8) 1966, 253-271. *Jager, S., & Wilkening, F. (2001). Development of cognitive averaging: When light and light make dark: Journal of Experimental Child Psychology Vol 79(4) Aug 2001, 323-345. *Knehr, C. A., & Lorenz, R. J. (1964). Subjective color: A new method of producing the phenomenon: Journal of Psychology: Interdisciplinary and Applied 58(2) 1964, 353-356. *Kraft, J. M. (1997). Changes in colorimetric purity discrimination and saturation perception across the life span. Dissertation Abstracts International: Section B: The Sciences and Engineering. *Long, F., Yang, Z., & Purves, D. (2006). Spectral statistics in natural scenes predict hue, saturation, and brightness: PNAS Proceedings of the National Academy of Sciences of the United States of America Vol 103(15) Apr 2006, 6013-6018. *Madsen, V., Valkiunas, G., Iezhova, T. A., Mercade, C., Sanchez, M., & Osorno, J. L. (2007). Testosterone levels and gular pouch coloration in courting magnificent frigatebird (Fregata magnificens): Variation with age-class, visited status and blood parasite infection: Hormones and Behavior Vol 51(1) Jan 2007, 156-163. *Mahon, L. E., & Vingrys, A. J. (1996). Normal saturation processing provides a model for understanding the effects of disease on color perception: Vision Research Vol 36(18) Sep 1996, 2995-3002. *McCamy, C. S. (2003). Colors of Some Small Figures on Colored Grounds: Color Research and Application Vol 28(4) Aug 2003, 242-250. *McGregor, D. (1936). Sensitivity of the eye to the saturation of colors: Journal of Experimental Psychology Vol 19(5) Oct 1936, 525-546. *Nayatani, Y. (2003). A Modified Opponent-Colors Theory Considering Chromatic Strengths of Various Hues: Color Research and Application Vol 28(4) Aug 2003, 284-297. *Nayatani, Y., & Nakajima, M. (1996). Prediction of the Helmholtz-Kohlrausch effect (VCC method) using the Swedish NCS System: Color Research and Application Vol 21(4) Aug 1996, 269-276. *Nayatani, Y., & Nakajima, M. (1996). Prediction of the Helmholtz-Kohlrausch effect using the CIELUV formula: Color Research and Application Vol 21(4) Aug 1996, 252-268. *Panek, D. W., & Stevens, S. S. (1966). Saturation of red: A prothetic continuum: Perception & Psychophysics 1(2) 1966, 59-66. *Peirce, J. W. (2007). The potential importance of saturating and supersaturating contrast response functions in visual cortex: Journal of Vision Vol 7(6) 2007, 1-10. *Pitts, M. A., Troup, L. J., Volbrecht, V. J., & Nerger, J. L. (2005). Chromatic perceptive field sizes change with retinal illuminance: Journal of Vision Vol 5(5) 2005, 435-443. *Solomons, L. M. (1896). The saturation of colors: Psychological Review Vol 3(1) Jan 1896, 50-56. *Spaulding, K. E., Woolfe, G. J., & Joshi, R. L. (2003). Extending the Color Gamut and Dynamic Range of an sRGB Image Using a Residual Image: Color Research and Application Vol 28(4) Aug 2003, 251-266. *Stabell, B., & Stabell, U. (1996). Peripheral colour vision: Effects of rod intrusion at different eccentricities: Vision Research Vol 36(21) Nov 1996, 3407-3414. *Stewart, N., & Morin, C. (2007). Dissimilarity is used as evidence of category membership in multidimensional perceptual categorization: A test of the similarity-dissimilarity generalized context model: The Quarterly Journal of Experimental Psychology Vol 60(10) Oct 2007, 1337-1346. *Stromeyer, C. F., III, Gowdy, P. D., Chaparro, A., & Kronauer, R. E. (1999). Second-site adaptation in the red-green detection pathway: Only elicited by low-spatial-frequency test stimuli: Vision Research Vol 39(18) Sep 1999, 3011-3023. *van den Berg, R., Roerdink, J. B. T. M., & Cornelissen, F. W. (2007). On the generality of crowding: Visual crowding in size, saturation, and hue compared to orientation: Journal of Vision Vol 7(2) 2007, 1-11. *Wuerger, S. M. (1996). Color appearance changes resulting from iso-luminant chromatic adaptation: Vision Research Vol 36(19) Oct 1996, 3107-3118. *Zemach, I., Chang, S., & Teller, D. Y. (2007). Infant color vision: Prediction of infants' spontaneous color preferences: Vision Research Vol 47(10) May 2007, 1368-1381. Category:Chromaticity Category:Color Color perception